class_docstr: Standalone Multiply-and-accumulate metric. Provides a lower bound of the
  computational cost of a model in a hardware-independent way by
  computing the number of multiplications. Currently supports only
  Linear or Conv2d modules. Other operations are ignored.
docstr: Creates an instance of the MAC metric.
docstr_tok: ["Creates","an","instance","of","the","MAC","metric","."]
code: def __init__(self):
      """
      Creates an instance of the MAC metric.
      """
      self.hooks = []
      self._compute_cost: Optional[int] = 0
  
imports: from torch.nn import Module
  from typing import List, Optional
  from torch import Tensor
  from avalanche.evaluation import Metric, PluginMetric, GenericPluginMetric
label_desc: Use image node_id 1 to create a new MAC object from inherited base classes: Metric with example: obj = MAC()